• Journal of Forest and Environmental Science
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• 제24권3호
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• pp.143-149
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• 2008

We conduct economic analysis of the snow damage on sugi (Cryptomeria japonica) forest stands in Toyama Prefecture, Japan. We utilize a single tree and distant independent growth simulator called "Silv-Forest." With this growth simulator, we developed an optimization model by dynamic programming, called DP-Silv (Dynamic Programming Silv-Forest). The MS-PATH (multiple stage projection alternative technique) algorithm was embedded as a searching algorithm of dynamic programming. The height / DBH ratio was used to constrain the thinning regime for snow damage protection. The optimal rotation age turned out to be 65 years for the non-restricted case, while it was 50 years for the restricted case. The difference in NPV of these two cases as the induced costs ranged from 179,867 to 1,910,713yen/ha over the rotation age of 20 to 75 years. Under the optimal rotation of 65 years, the cost became 914,226 yen/ha. The estimated annual payment based on the difference in NPV, was from 9,869 yen/ha/yr to 85,900 yen/ha/yr. All in all, 10,000 yen/ha/yr to 20,000 yen/ha/yr seems to cover the payment from the rotation age of 35 to 75 years.

• 대기
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• 제24권2호
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• pp.151-158
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• 2014

This study investigated a method for the discrimination of precipitation type using thickness of geopotential height at 1000~850 hPa and improved Matsuo's scheme over South Korea using 7 upper-level observations data during winter time from 2003 to 2008. With this research, it was suggested that thickness between snow and rain should range from 1281 to 1297 gpm at 1000~850 hPa. This threshold was suitable for determining precipitation type such as snow, sleet and rain and it was verified by investigation at 7 upper-level observation and 10 surface observation data for 3 years (2009~2011). In addition, precipitation types were separated properly by Matsuo's scheme and its improved one, which is a fuction of surface air temperature and relative humidity, when they lie in mixed sectors. Precipitation types in the mixed sector were subdivided into 5 sectors (rain, rain and snow, snow and rain, snow, and snow cover). We also present the decision table for monitoring and predicting precipitation types using model output of Korea Local Analysis and Prediction System (KLAPS) and observation data.

• 대기
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• 제28권2호
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• pp.153-162
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• 2018

The statistical prediction model for wintertime surface air temperature, that is based on snow cover extent and Arctic sea ice concentration, is updated by considering $El-Ni{\tilde{n}}o$ Southern Oscillation (ENSO) and Quasi-Biennial Oscillation (QBO). These additional factors, representing leading modes of interannual variability in the troposphere and stratosphere, enhance the seasonal prediction over the Northern Hemispheric surface air temperature, even though their impacts are dependent on the predicted month and region. In particular, the prediction of Korean surface air temperature in midwinter is substantially improved. In December, ENSO improved about 10% of prediction skill compared without it. In January, ENSO and QBO jointly helped to enhance prediction skill up to 36%. These results suggest that wintertime surface air temperature in Korea can be better predicted by considering not only high-latitude surface conditions (i.e., Eurasian snow cover extent and Arctic sea ice concentration) but also equatorial sea surface temperature and stratospheric circulation.

• 산업경영시스템학회지
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• 제45권2호
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• pp.20-29
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• 2022

This study intends to present a traffic node-based and link-based accident prediction models using XGBoost which is very excellent in performance among machine learning models, and to develop those models with sustainability and scalability. Also, we intend to present those models which predict the number of annual traffic accidents based on road types, weather conditions, and traffic information using XGBoost. To this end, data sets were constructed by collecting and preprocessing traffic accident information, road information, weather information, and traffic information. The SHAP method was used to identify the variables affecting the number of traffic accidents. The five main variables of the traffic node-based accident prediction model were snow cover, precipitation, the number of entering lanes and connected links, and slow speed. Otherwise, those of the traffic link-based accident prediction model were snow cover, precipitation, the number of lanes, road length, and slow speed. As the evaluation results of those models, the RMSE values of those models were each 0.2035 and 0.2107. In this study, only data from Sejong City were used to our models, but ours can be applied to all regions where traffic nodes and links are constructed. Therefore, our prediction models can be extended to a wider range.

• Ocean and Polar Research
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• 제26권3호
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• pp.439-451
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• 2004

Total solar irradiance (750), total UV irradiunce (TUV) and erythemal UV irradiance (EUV) measured at King Sejong station $(62.22^{\circ}S,\;58.78^{\circ}W)$ in west Antarctica have been used together with total ozone, cloud amount and snow cover to examine the effects of ozone, cloud and snow surface on these surface solar inadiunce over the period of 1998-2003. The data of three solar components for each scan were grouped by cloud amount, n in oktas $(0{\leq}n<3,\;3{\leq}n<4,\;4{\leq}n<5,\;5{\leq}n<6,\;6{\leq}n<7\;and\;7{\leq}n<8)$ and plotted against solar zenith angle (SZA) over the range of $45^{\circ}\;to\;75^{\circ}$. The radiation amplification factor (RAE) is used to quantify ozone effect on EUV. RAF of EUV decreases from 1.51 to 0.94 under clear skies but increases from 0.94 to 1.85 under cloudy skies as SZA increases, and decreases from 1.51 to 1.01 as cloud amount increases. The effects of cloud amount and snow surface on EUV are estimated as a function of SZA and cloud amount after normalization of the data to the reference total ozone of 300 DU. In order to analyse the transmission of solar radiation by cloud, regression analyses have been performed for the maximum values of solar irradiance on clear sky conditions $(0{\leq}n<3)$ and the mean values on cloudy conditions, respectively. The maximum regression values for the clear sky cases were taken to represent minimum aerosol conditions fur the site and thus appropriate for use as a normalization (reference) factor for the other regressions. The overall features for the transmission of the three solar components show a relatively high values around SZAs of $55^{\circ}\;and\;60^{\circ}$ under all sky conditions and cloud amounts $4{\leq}n<5$ and $5{\leq}n<6$. The transmission is, in general, the largest in TUV and the smallest in EUV among the three components of the solar irradiance. If the ground is covered with snow on partly cloudy days $(6{\leq}n<7)$, EUV increases by 20 to 26% compared to snow-free surface around SZA $60^{\circ}-65^{\circ}$, due to multiple reflections and scattering between the surface and the clouds. The relative difference between snow surface and snow-free surface slowly increases from 9% to 20% as total ozone increases from 100 DU to 400 DU under partly cloud conditions $(3{\leq}n<6)$ at SZA $60^{\circ}$. The snow effects on TUV and TSO are relatively high with 32% and 34%, respectively, under clear sky conditions, while the effects changes to 36% and 20% for TUV and TSO, respectively, as cloud amount increases.

• 아시안잔디학회지
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• 제24권1호
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• pp.9-15
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• 2010

2008~2009 겨울 동안 강원도와 전라북도 소재 골프장에서 분리한 황색마름병원균(Rhizoctonia cerealis Van der Hoeven)과 설부갈색소립균핵병원균(이하 설부병원균)(Typhlua incarnata Lasch ex Fr.)에 대한 화본과 식물과 잔디 종(품종)의 저항성이 실내에서 평가되었다. 분리균주의 병원성 검정결과 대부분의 잔디와 화본과 식물에 병을 일으켰지만 균주간의 병원력 차이도 발견되었다. 황색마름 병균은 잔디의 지제부위를 통해 감염하여 연한 갈색의 원형 반점 증상을 보이다가 진전되면 적색을 띄다가 결국 진한 갈색의 증상으로 나타났다. 설부병 증상은 수침형 반점으로 시작해서 전체 식물체를 갈색으로 고사시켰는데, 대부분 감염부위에서 흰색의 균사체가 식물체와 토양을 뒤덮었고 진전되면 다양한 크기의 갈색과 검은색의 독특한 균핵을 형성하였다. 병 발생은 습실기간이 길어질수록 증가하는 경향이었다. 화본과 작물과 잔디의 종(품종)간에는 병원균의 병원력에 차이도 나타났으며 두 병원균에 대해 양적인 차이를 보였다.

• 대한원격탐사학회지
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• 제39권6_1호
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• pp.1497-1503
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• 2023

본 연구는 Near-UltraViolet (UV) 파장에서의 지표면 반사도 산출 시 발생하는 구름과 적설의 분류 한계를 극복하기 위해 Geostationary Environmental Monitoring Spectrometer (GEMS)와 Advanced Meteorological Imager (AMI) 위성의 구름 자료를 융합하여 적설역에서의 지표면 반사도 품질을 향상시키는 방법을 제안한다. GEMS 구름 산출물과 AMI 구름탐지 자료를 기반으로 융합 구름자료를 생산하였으며, 이를 GEMS 지표면 반사도 산출에 적용하였다. 그 결과 적설역에서 GEMS 구름 산출물만 사용한 경우에 비해 미산출이 개선되었으며 이는 전체 관측 영역에서 약 17%의 개선 효과를 확인하였다. 본 연구 결과는 융합 구름자료를 활용하여 적설역에서 지속적으로 발생했던 지표면 반사도 미산출 문제를 개선할 수 있음을 입증하며, 이를 통해 산출된 고품질의 지표면 반사도를 기반으로 타 Level-2 산출물의 품질향상을 기대할 수 있다.

• 대기
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• 제23권1호
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• pp.73-83
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• 2013

In recent several years, East Asia, Europe and North America have suffered successive cold winters and a number of historical records on the extreme weathers are replaced with new record-breaking cold events. As a possible explanation, several studies suggested that cryospheric conditions of Northern Hemisphere (NH), i.e. Arctic sea-ice and snow cover over northern part of major continents, are changing significantly and now play an active role for modulating midlatitude atmospheric circulation patterns that could bring cold winters for some regions in midlatitude. In this study, a dynamical seasonal prediction system for NH winter is newly developed using the snow depth initialization technique and statistically predicted sea-ice boundary condition. Since the snow depth shows largest variability in October, entire period of October has been utilized as a training period for the land surface initialization and model land surface during the period is continuously forced by the observed daily atmospheric conditions and snow depths. A simple persistent anomaly decaying toward an averaged sea-ice condition has been used for the statistical prediction of sea-ice boundary conditions. The constructed dynamical prediction system has been tested for winter 2012/13 starting at November 1 using 16 different initial conditions and the results are discussed. Implications and a future direction for further development are also described.

• 대기
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• 제20권4호
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• pp.415-426
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• 2010

A Land cover map over East Asian region (Kongju national university Land Cover map: KLC) is classified by using support vector machine (SVM) and evaluated with ground truth data. The basic input data are the recent three years (2006-2008) of MODIS (MODerate Imaging Spectriradiometer) NDVI (normalized difference vegetation index) data. The spatial resolution and temporal frequency of MODIS NDVI are 1km and 16 days, respectively. To minimize the number of cloud contaminated pixels in the MODIS NDVI data, the maximum value composite is applied to the 16 days data. And correction of cloud contaminated pixels based on the spatiotemporal continuity assumption are applied to the monthly NDVI data. To reduce the dataset and improve the classification quality, 9 phenological data, such as, NDVI maximum, amplitude, average, and others, derived from the corrected monthly NDVI data. The 3 types of land cover maps (International Geosphere Biosphere Programme: IGBP, University of Maryland: UMd, and MODIS) were used to build up a "quasi" ground truth data set, which were composed of pixels where the three land cover maps classified as the same land cover type. The classification results show that the fractions of broadleaf trees and grasslands are greater, but those of the croplands and needleleaf trees are smaller compared to those of the IGBP or UMd. The validation results using in-situ observation database show that the percentages of pixels in agreement with the observations are 80%, 77%, 63%, 57% in MODIS, KLC, IGBP, UMd land cover data, respectively. The significant differences in land cover types among the MODIS, IGBP, UMd and KLC are mainly occurred at the southern China and Manchuria, where most of pixels are contaminated by cloud and snow during summer and winter, respectively. It shows that the quality of raw data is one of the most important factors in land cover classification.

• 한국수자원학회논문집
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• 제55권12호
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• pp.1125-1135
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• 2022

적설에 의한 피해는 자주 발생하지 않지만 발생하면 광범위한 지역에 피해를 준다. 적설에 의한 피해를 예방하기 위해서는 지역별로 피해를 유발하는 적설심을 미리 파악해 둘 필요가 있다. 하지만 관측하고 있는 적설심은 특정 관측지점으로 한정되어 피해를 유발하는 지역별 피해유발적설심을 파악하는데 어려움이 있다. 이를 극복하기 위한 일반적인 방법은 관측지점의 적설을 보간하여 공간적으로 확대하는 것이다. 하지만 이것은 매우 적은 자료를 가지고 고도 등 지형적인 특성이 다른 넓은 영역을 통계적으로 추론해야 하는 한계로 인해 지역에 대한 피해유발 피해유발적설심의 구명에 더 혼란을 주기도 한다. 이를 보완하기 위해서는 넓은 영역을 관측하는 위성영상을 활용할 수 있으며, 그 중에서도 합성개구레이더(Synthetic Aperture Radar; SAR)를 이용한 위상차분 간섭기법(DInSAR)을 활용할 수 있다. 위상간섭영상은 두 개의 다른 시기에 측정된 합성개구레이더 영상의 위상간섭을 이용한 것으로 일반적으로 미세한 지형의 변화를 추적할 때 사용되기도 한다. 본 연구에서는 유럽우주국(ESA)에서 운영하는 Sentinel-1B 위성의 dual polarimetric IW 모드 C-band SAR 데이터를 사용하여 DInSAR 분석을 수행하여 적설심의 공간분포를 추정하였다. 또한 정지궤도복합위성 천리안 2호(GK-2A)의 L2 적설심 추정 자료를 이용하여 비교하였다. 적용 결과, 적설예측의 정확도는 격자별로 계산할 경우, DInSAR 는 약 0.92%, GK-2A 는 약 0.71% 를 나타내 DInSAR의 적용성이 높게 나타났다. 즉, DInSAR 방법을 이용하여 계산된 적설심과 기상관측소에서 관측된 적설심을 공간보간하여 비교한 결과, 적설의 분석 결과 적설심을 과대추정하는 경우가 발생하기는 했으나, 적설심의 공간분포를 추정하는데 충분한 정보를 제공했으며, 이러한 방법으로 파악된 적설심의 공간분포는 실제 피해발생지역의 적설심을 보다 정확하게 추정하는데 기여할 수 있으며, 이것은 지역별 피해유발적설심을 파악하는데 도움이 될 것이다.